Reflection's Beam Is the New Open-Weight Model Everyone Is Talking About

Reflection AI's new open-weight model, Beam, features 501 billion total parameters and a sparse mixture-of-experts architecture that activates 23 billion parameters per token. The author examines Reflection's claims of matching GLM-5.2 on reasoning benchmarks with three to four times less inference compute, noting that while active parameter counts reduce compute costs, the model's large memory footprint still requires significant hardware resources. Additionally, the author analyzes the published deployment sizes across different quantization formats and emphasizes the importance of evaluating memory requirements before deployment. Open article →